Active regulation of the epidermal calcium profile

A distinct calcium profile is strongly implicated in regulating the multi-layered structure of the epidermis. However, the mechanisms that govern the regulation of this calcium profile are currently unclear. It clearly depends on the relatively impermeable barrier of the stratum corneum (passive regulation) but may also depend on calcium exchanges between keratinocytes and extracellular fluid (active regulation). Using a mathematical model that treats the viable sublayers of unwounded human and murine epidermis as porous media and assumes that their calcium profiles are passively regulated, we demonstrate that these profiles are also actively regulated. To obtain this result, we found that diffusion governs extracellular calcium motion in the viable epidermis and hence intracellular calcium is the main source of the epidermal calcium profile. Then, by comparison with experimental calcium profiles and combination with a hypothesised cell velocity distribution in the viable epidermis, we found that the net influx of calcium ions into keratinocytes from extracellular fluid may be constant and positive throughout the stratum basale and stratum spinosum, and that there is a net outflux of these ions in the stratum granulosum. Hence the calcium exchange between keratinocytes and extracellular fluid differs distinctly between the stratum granulosum and the underlying sublayers, and these differences actively regulate the epidermal calcium profile. Our results also indicate that plasma membrane dysfunction may be an early event during keratinocyte disintegration in the stratum granulosum

Local versus organic: a turn in consumer preferences and willingness-to-pay

Demand for local food in the United States has significantly increased over the last decade. In an attempt to understand the drivers of this demand and how they have changed over time, we investigate the literature on organic and local foods over the last few decades. We focus our review on studies that allow comparison of characteristics now associated with both local and organic food. We summarize the major findings of these studies and their implications for understanding drivers of local food demand. Prior to the late 1990s, most studies failed to consider factors now associated with local food, and the few that included these factors found very little support for them. In many cases, the lines between local and organic were blurred. Coincident with the development of federal organic food standards, studies began to find comparatively more support for local food as distinct and separate from organic food. Our review uncovers a distinct turn in the demand for local and organic food. Before the federal organic standards, organic food was linked to small farms, animal welfare, deep sustainability, community support, and many other factors that are not associated with most organic foods today. Based on our review, we argue that demand for local food arose largely in response to corporate cooptation of the organic food market and the arrival of “organic lite.” This important shift in consumer preferences away from organic and toward local food has broad implications for the environment and society. If these patterns of consumer preferences prove to be sustainable, producers, activists, and others should be aware of the implications that these trends have for the food system at large

The Labour Supply of Sex Workers in Cape Town

Traditional labour economics predicts that the supply of labour will increase as earnings increase. However, labour supply need not be positive, especially if workers make decisions based on short-term income targets. Income targeting may best describe jobs where workers decide on working hours and where wages are uncorrelated across days. This paper examines the labour supply of sex workers in Cape Town, whose working conditions largely fulfill these criteria. Contrary to traditional economic theory, we find evidence of a negative labour supply curve.Labour supply, sex workers, hyperbolic discounting

Do emotional faces capture attention, and does this depend on awareness? Evidence from the visual probe paradigm

The visual probe (VP) paradigm provides evidence that emotional stimuli attract attention. Such effects have been reported even when stimuli are presented outside of awareness. These findings have shaped the idea that humans possess a processing pathway that detects evolutionarily significant signals independently of awareness. Here, we addressed 2 unresolved questions: First, if emotional stimuli attract attention, is this driven by their affective content, or by low-level image properties (e.g., luminance contrast)? Second, does attentional capture occur under conditions of genuine unawareness? We found that observers preferentially allocated attention to emotional faces under aware viewing conditions. However, this effect was best explained by low-level stimulus properties, rather than emotional content. When stimuli were presented outside of awareness (via continuous flash suppression or masking), we found no evidence that attention was directed toward emotional face stimuli. Finally, observer's awareness of the stimuli (assessed by d') predicted attentional cuing. Our data challenge existing literature: First, we cast doubt on the notion of preferential attention to emotional stimuli in the absence of awareness. Second, we question whether effects revealed by the VP paradigm genuinely reflect emotion-sensitive processes, instead suggesting they can be more parsimoniously explained by low-level variability between stimuli. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

On the Complexity and Performance of Parsing with Derivatives

Current algorithms for context-free parsing inflict a trade-off between ease of understanding, ease of implementation, theoretical complexity, and practical performance. No algorithm achieves all of these properties simultaneously. Might et al. (2011) introduced parsing with derivatives, which handles arbitrary context-free grammars while being both easy to understand and simple to implement. Despite much initial enthusiasm and a multitude of independent implementations, its worst-case complexity has never been proven to be better than exponential. In fact, high-level arguments claiming it is fundamentally exponential have been advanced and even accepted as part of the folklore. Performance ended up being sluggish in practice, and this sluggishness was taken as informal evidence of exponentiality. In this paper, we reexamine the performance of parsing with derivatives. We have discovered that it is not exponential but, in fact, cubic. Moreover, simple (though perhaps not obvious) modifications to the implementation by Might et al. (2011) lead to an implementation that is not only easy to understand but also highly performant in practice.Comment: 13 pages; 12 figures; implementation at http://bitbucket.org/ucombinator/parsing-with-derivatives/ ; published in PLDI '16, Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation, June 13 - 17, 2016, Santa Barbara, CA, US

Patterns of Scalable Bayesian Inference

Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this challenge, there has been considerable recent work based on varying assumptions about model structure, underlying computational resources, and the importance of asymptotic correctness. As a result, there is a zoo of ideas with few clear overarching principles. In this paper, we seek to identify unifying principles, patterns, and intuitions for scaling Bayesian inference. We review existing work on utilizing modern computing resources with both MCMC and variational approximation techniques. From this taxonomy of ideas, we characterize the general principles that have proven successful for designing scalable inference procedures and comment on the path forward